Analysis Of UHI In South Korea

I ran a post earlier about UHI in South Korea. A study by two Korean scientists found that over half of the warming reported in Korea since 1954 was a result of UHI. In many cities, the effect of UHI was to add more than a degree to temperatures over the period they had analysed, 1954-2008.

I was already aware that GISS tended to allow only about 0.2C for UHI in other cities I had examined previously, so I was curious to find out what allowance they were making in Korea.

There are ten stations currently in use in South Korea, which are in the GHCN database, that in turn is used by GISS. These are all listed in Appendix A.

First, a brief explanatory note. GHCN collect temperature data, which they then put through a homogenisation algorithm, which may result in adjustments. These adjusted numbers are then used by GISS, who then put then through their own homogenisation process, which is designed to make allowance for UHI effects – more detail here.

The figures below compare the raw data with the “after GISS adjustment” data, so the resulting differences are due to a combination of both GHCN and GISS adjustments.

The study only listed Pohang, Seoul and Mokpo in the abstract. The other cities, marked as n/a, may be in the full paper, but it is paywalled!

The following points are noteworthy:-

Out of the ten stations, only one, Ullungdo, is rural.

The typical adjustment from raw to “UHI adjusted” is much less than the study found.

The average adjustment for the nine urban sites is a paltry 0.05C

There is, incredibly, no adjustment at all for Seoul, while the adjustments at Mokpo and Cheju have actually added to the warming trend.

At the only rural station, Ullungdo, the GHCN adjustment has reduced the 1954 temperature, thus adding to the warming trend.

It is often claimed that station moves out of city centres and into airports can offset UHI. This is not the case in South Korea, as only one site, Chunchon, is listed as an airport site on the GISS station list.

Conclusions

Since the 1940’s, there has been a massive increase in urbanisation in South Korea. The country’s population has risen from 20 million in 1949, to over 50 million today. Between 1945 and 1985, it has been estimated that the urban population increased from 14% to 65% of the total population, which would imply more than a tenfold increase in actual numbers.

On top of that, industrialisation and technology have made these cities unrecognisable from 50 years ago. It is inconceivable that these factors would not have created a significant increase in UHI effect over the years.

Which all raises the question, why are GISS allowing for so little? With only one rural station, their temperature calculations for the whole country are heavily skewed towards these urban sites, and therefore must be viewed with considerable scepticism.

What is true for South Korea is also true for much of the region, as mass urbanisation and industrialisation have similarly affected many other countries there, such as China. Has correct allowance been made for UHI in these?

Urban areas are heavily overrepresented in the siting of temperature stations: less than 1% of the globe is urban but 27% of the Global Historical Climatology Network Monthly (GHCN-M) stations are located in cities with a population greater than 50,000.

23 thoughts on “Analysis Of UHI In South Korea”

Urban areas are heavily overrepresented in the siting of temperature stations: less than 1% of the globe is urban but 27% of the Global Historical Climatology Network Monthly (GHCN-M) stations are located in cities with a population greater than 50,000.

It’s even worse than that. In the US HCN I was hard-pressed to find a record -any- record that wasn’t either inside city limits or within a mile of a US Post Office. I only managed to get through several hundred sites, but we’ve heard several times that the largest -changes- in the UHI should come about at the lower end of the scale.

You don’t think that perhaps Pohang, which was a FISHING village until about 1960, might suffer from UHI as the home of Pohang Steel company just possibly, apart from the fact the population must have grown by a factor of 1000 in the interim

Ah, nights gazing across the beach at Pohang….straight at one of the largest steelplants in the far east…..

I just came back from the shopping centre. My car was sitting in the lot in the sun.
When I came out and got into my car the temperature in my car read 31C.
The weather station showed 25C. If that is not an example of UHI, then what is?

I’m reminded of McKittrick’s paper showing that there’s a strong correlation between warming and economic activity.

It 2006, total U.S. energy consumption was estimated (according to DOE/EIA) to be 97.1 quadrillion BTUs, which when converted to “watts” type measurements is
equivalent to 3.25 x 10 ^12 watts generated continuously over the course of a year.
If we divide that by the surface area of the U.S. in meters, we get 0.33 watts per sq. meter.

Now, compare that the the total radiative forcing from increasing greenhouse gas concentrations supposedly operating today, which (according to the IPCC) is

somewhere around 1.6 W/m2.

At this point, we might conclude that the waste heat generation (0.33 W/m2) is only about 20% of the radiative forcing from increasing CO2 (1.6 W/m2).
We have most of our thermometers where people live. People mostly live in urban areas.
Some temperature measurements will be measuring growth of urban areas
rather than effects of greenhouse gases:

Most people are aware that the world’s population has quadrupled,
from about 1.6 billion to about
6.5 billion in the last century. , and urban populations have more
than quadrupled. The world’s energy use has gone up by a factor of
10 over the last century, again most of that increase being in
urban areas. I get a rough estimate of 0.26 watts per square meter
heat energy produced over the world. Assuming that 3% of the land surface is
Urban, and 30% of the earth’s surface is land, I get
29 watts per square meter assuming most of that heat is produced in
urban areas. And that has
gone up by a factor of 10 since 1900, from 2.9 to 29 watts, way more than the 1.6 watts theoretically due to greenhouse gases.. There should have been a long negative correction for the urban heat island effect over the last centure, and yet, as Steve McIntyre has pointed out,

GISS says that the +/- averages out OVER THE WORLD. Seems like there is too much desire for automation and too little for manual inspection and data correction: forget assuming that the bulk averages out, spend the time and effort to look at each station and apply individual, appropriate corrections! Let’s get our taxpayers’ money out of these university degrees.

Old school is sometimes best. Just now the accident investigation group is suggesting that too much reliance on automation, i.e. autopilot, may be a factor in the San Francisco South Korean crash of the other week, that not enough “hands-on” experience led to an inability to correctly judge what was going on.

Sounds like the IPCC: let computers and statisticians with computers do it. It’s easier, we don’t understand it, but, again it is easier.

Why not simply use the raw temperature data? All these adjustments and corrections are, to a substantial extent, falsifications. No one should have to depend upon falsifications for scientific data, let alone for justifying policy decisions. I remember earlier articles on this site showing the actual temperature increase due to UHI, so raw temperature data from urban areas (which is most of them nowadays) should have an asterisk that leads to a notation of the likely temperature had that location been in the country (which most actual land still is). The raw data should be still available and should be the foundation upon which any extrapolations or deductions are made, even if allowances must be made for UHI or other conditions. I could also go on and on about “anomalies” or departures from an average that is impossible reliably to establish, but that’s for another time.

It is refreshing to see actual science being done. I suspect as more venture out from the religion, the backlash will become more severe. BUt eventually we will have a good picture of what is happening with temperatures around the globe.

GISS says that the +/- averages out OVER THE WORLD.
+++++++++++++++++++++++++++++++++++++++++++++++++++
Unfortunately, individual countries (such as Oz) look at and make decisions based on the adjustments FOR THEIR COUNTRY with little regard for the global figures.

Raising the temps in Oz and lowering them in, say, Antactica could certainly average out the global adjustments but makes Oz look hotter. Cue the greenies and pollies making decisions on such distorted figures.

Dr. John M. Ware says:
July 10, 2013 at 5:43 pm
Why not simply use the raw temperature data? All these adjustments and corrections are, to a substantial extent, falsifications.

Exactly!

I say again: I drive in to town and observe the temperature to increase by 5 to 9 F warmer than 15 miles from town. So for every UHI thermometer there should be a rural thermometer by which to make a comparison. some areas will be similar to rural while others will greatly be varied by the simple fact of micorclimates. The UHI temperature is what it is; it is insane to guesstimate some adjustment on some B.S. formula.

The climate change issue is a non issue. We as a species live on all continents, warm and cold, dry and wet. If warm is so bad why do all the northerner types head for the tropics during winter? And why is snow skiing so popular? -65 in West Yellowstone and people are on the trails. Climate change is a non issue.

Obviously, the use and interpretation of the raw data is preferable so as to prevent one from falling into the trap of simply interpreting the effects of adjustments and unexpected bias caused by the adjustments.

If CO2 is a well mixed gas and if global warming is a global issue, why do we need so many weather monitoring stations? What we need is quality not quantity.

I would have tjhought that the first task would be to undertake a thorough audit of all weather monitoring stations world wide, and identify those that are properly sited and those that are truly rural and have been so from inception. One needs to identify station data whereby the only anthropogenic change and influence is the atmosphere, and not change of land use (by which I include urbanisation and of course, nearby crop spraying). A proper physical inspection and site survey is required, and we need to ascertain whether in the case of the rural stations there have been any material changes in vegation (including the siting of trees) over the years, and remove ones which have been adversely affected by such change .

Thereafter, one would look at the resultant class to identify those with the longest uninterupted record. Any change of instrumentation would be the end of one record and the beginning of a new record. There should be no attempt at splicing one onto the other. Ditto any geographical relocation of the station, although I consider that we should not use any station that has been the subject of geegraaphical relocation.

In theory, just a handful of high quality stations in each country should be better representaive of temperature changes than a data set comprosed predominantly by poor quality stations and which thereby require some form of adjustment/homogenisation..

PS. a good article Paul; yet another example where it would appear that the Team have failed to get a grips with UHI.

Just a thought, but why are we concerned with what has happened to temperatures over the last century?

If they have gone up, then so what? It has happened, we cannot undo it, and anyway would we want to if we could?

Would we want to return the cold 70’s, the dustbowl 30’s or the 19thC LIA?

The only thing that should matter is how they will change in future. So, as others have suggested, why don’t we concentrate on a small number of quality stations, throw out the adjustment ridden old data, and start from scratch?

Folks should keep in mind that the temperature measuring stations are performing their original goal quite well and accurately. They were intended to provide information about local climatic conditions. An accuracy of plus or minus a degree or two Celsius is adequate, understanding that morning to afternoon temperature swings of ten degrees is common. High to low over the course of a year could easily be fifty degrees Celsius. Thermometers with accuracy better than half a degree Celsius met the requirement for this job.

Keep in mind that the folks who designed the older temperature monitoring system were not dummys. They understood the difficult issues in obtaining accurate temperature measurement. Overall measurement accuracy is never as good as the calibration accuracy of the measuring instrument. How and where it is mounted, sheltered, and read effect the accuracy of individual temperature readings. Though the thermometers used were often calibrated to an accuracy of around one fourth of a degree Celsius and a common design for sheltering them were used, no one expected total system accuracy to be anywhere near good enough to reliably measure long term temperature trends as low as have been calculated.

The problem in climate analysis comes from attempting to use that local climate information to detect temperature trends that require much greater accuracy than the design accuracy of the monitoring system. Additionally, the question of Urban Heat Island was not a problem from the perspective of the original system design. When folks wanted know what the temperature of New York City is (or even was in the past), they wanted to know the actual value, not what it would have been if the city was not there!

So the actual situation is that we do not have measurement data adequate to characterize historic temperature trends of around two degrees Celsius or less, at least not until the recently constructed high accuracy monitoring sites were brought on line. Unfortunately, they have been on line too short a length time to useful yet for reliable long term trend identification.

Acronym timeout.
Forgive me but I am not one of the cognoscenti on this blog.
Whenever an acronym is used in a blog entry, It would be a good thing to state what the acronym stands for. Of course many of you will know this, but for us occasional visitors, these new terms keep getting in the way of understanding the substance of the posting.

So what does UHI stand for?

Thank you,
Alice

[Reply: It means the “Urban Heat Island” effect. Maybe this will help in future. — mod.]

The Korea Meteorological Administration (KMA) has nice English overviews of monthly and seasonal temperature data and trends of Seoul and Korea on its website:http://web.kma.go.kr/eng/aboutkma/notice.jsp. The Seoul data goes back to 1908; the Korea data goes back to 1973.

For Seoul and Korea, there is an upward trend of the mean temperature for all four season. However, the data on the KMA websites shows that the trend in winter is steeper than in summer. Spring and fall are somewhere in between. Furthermore, for all seasons, the upward trend of the minimum temperature is also steeper than the trend of the maximum temperature (if present). In fact, maximum summer temperature of Seoul is showing a very slight downward trend since its recording began in 1903. The minimum temperature shows an upwards trends, giving the mean temperature an upward trend as well.